On Sparse Covers of Minor Free Graphs, Low Dimensional Metric Embeddings, and other applications.
Arnold FiltserPublished in: CoRR (2024)
Keyphrases
- low dimensional
- high dimensional
- graph embedding
- metric space
- high dimensional data
- embedding space
- dimensionality reduction
- manifold learning
- maximum common subgraph
- dimension reduction
- random projections
- sparse metric learning
- vector space
- laplacian matrix
- euclidean space
- data points
- principal component analysis
- gaussian graphical models
- multidimensional scaling
- sparse representation
- underlying manifold
- similarity search
- distance measure
- metric learning
- graph databases
- graph matching
- linear subspace
- input space
- graph mining
- feature space
- nonlinear dimensionality reduction
- evaluation metrics
- sparse coding
- pairwise distances
- graph theoretic
- graph structure
- data sets
- distance metric
- low dimensional spaces
- nearest neighbor
- similarity measure